Model‐assisted identification of metabolic engineering strategies for Jatropha curcas lipid pathways

Efficient approaches to increase plant lipid production are necessary to meet current industrial demands for this important resource. While Jatropha curcas cell culture can be used for in vitro lipid production, scaling up the system for industrial applications requires an understanding of how growth conditions affect lipid metabolism and yield. Here we present a bottom‐up metabolic reconstruction of J. curcas supported with labeling experiments and biomass characterization under three growth conditions. We show that the metabolic model can accurately predict growth and distribution of fluxes in cell cultures and use these findings to pinpoint energy expenditures that affect lipid biosynthesis and metabolism. In addition, by using constraint‐based modeling approaches we identify network reactions whose joint manipulation optimizes lipid production. The proposed model and computational analyses provide a stepping stone for future rational optimization of other agronomically relevant traits in J. curcas.     

Long‐term persistence of wildlife populations in a pastoral area

Facilitating coexistence between people and wildlife is a major conservation challenge in East Africa. Some conservation models aim to balance the needs of people and wildlife, but the effectiveness of these models is rarely assessed. Using a case‐study approach, we assessed the ecological performance of a pastoral area in northern Tanzania (Manyara Ranch) and established a long‐term wildlife population monitoring program (carried out intermittently from 2003 to 2008 and regularly from 2011 to 2019) embedded in a distance sampling framework. By comparing density estimates of the road transect‐based long‐term monitoring to estimates derived from systematically distributed transects, we found that the bias associated with nonrandom placement of transects was nonsignificant. Overall, cattle and sheep and goat reached the greatest densities and several wildlife species occurred at densities similar (zebra, wildebeest, waterbuck, Kirk's dik‐dik) or possibly even greater (giraffe, eland, lesser kudu, Grant's gazelle, Thomson's gazelle) than in adjacent national parks in the same ecosystem. Generalized linear mixed models suggested that most wildlife species (8 out of 14) reached greatest densities during the dry season, that wildlife population densities either remained constant or increased over the 17‐year period, and that herbivorous livestock species remained constant, while domestic dog population decreased over time. Cross‐species correlations did not provide evidence for interference competition between grazing or mixed livestock species and wildlife species but indicate possible negative relationships between domestic dog and warthog populations. Overall, wildlife and livestock populations in Manyara Ranch appear to coexist over the 17‐year span. Most likely, this is facilitated by existing connectivity to adjacent protected areas, effective anti‐poaching efforts, spatio‐temporal grazing restrictions, favorable environmental conditions of the ranch, and spatial heterogeneity of surface water and habitats. This long‐term case study illustrates the potential of rangelands to simultaneously support wildlife conservation and human livelihood goals if livestock grazing is restricted in space, time, and numbers.     

A Bayes factor approach with informative prior for rare genetic variant analysis from next generation sequencing data

The discovery of rare genetic variants through next generation sequencing is a very challenging issue in the field of human genetics. We propose a novel region‐based statistical approach based on a Bayes Factor (BF) to assess evidence of association between a set of rare variants (RVs) located on the same genomic region and a disease outcome in the context of case‐control design. Marginal likelihoods are computed under the null and alternative hypotheses assuming a binomial distribution for the RV count in the region and a beta or mixture of Dirac and beta prior distribution for the probability of RV. We derive the theoretical null distribution of the BF under our prior setting and show that a Bayesian control of the false Discovery Rate can be obtained for genome‐wide inference. Informative priors are introduced using prior evidence of association from a Kolmogorov‐Smirnov test statistic. We use our simulation program, sim1000G, to generate RV data similar to the 1000 genomes sequencing project. Our simulation studies showed that the new BF statistic outperforms standard methods (SKAT, SKAT‐O, Burden test) in case‐control studies with moderate sample sizes and is equivalent to them under large sample size scenarios. Our real data application to a lung cancer case‐control study found enrichment for RVs in known and novel cancer genes. It also suggests that using the BF with informative prior improves the overall gene discovery compared to the BF with noninformative prior.     

Better survival after transcatheter aortic valve replacement by process improvements

ObjectiveThe aim of this study is to assess the effects on procedural, 30-day, and 1‑year all-cause mortality by a newly introduced quality improvement strategy in patients after transcatheter aortic valve replacement (TAVR).MethodsIn October 2015, a coherent set of quality improving interventions with respect to patient geriatric screening, general diagnostic examination and safety of the procedure was implemented at a single centre in the Netherlands. Patients undergoing TAVR in 2013–2018 were included for retrospective analysis. Mortality was assessed in the pre-quality improvement strategy cohort (January 2013 to October 2015; cohort A) and in the post-quality improvement strategy cohort (November 2015 to December 2018; cohort B). Logistic regression analysis was used to estimate the influence of patient and procedural characteristics on the results of the quality improvement strategy in terms of procedural, 30-day, and 1‑year all-cause mortality.ResultsIn total, 806 patients were analysed with 274 patients in cohort A and 532 patients in cohort B. After introduction of the quality improvement strategy, procedural (4.4% to 1.3%, p < 0.01), 30-day (8.4% to 2.7%, p < 0.01) and 1‑year (16.4% to 8.5%, p < 0.01) all-cause mortality significantly decreased. Multivariate regression analysis showed that the quality improvement strategy also significantly reduced 30-day (odds ratio [OR] 0.19, 95% confidence interval [CI] 0.09–0.42) and 1‑year (OR 0.38, 95% CI 0.24–0.61) all-cause mortality if corrected for patient characteristics.ConclusionStructural meetings on evaluation of outcomes highlight potential areas for improvement and subsequent outcome-based quality improvement initiatives can result in lower procedural, 30-day, and 1‑year all-cause mortality.Electronic supplementary materialThe online version of this article (10.1007/s12471-020-01526-7) contains supplementary material, which is available to authorized users.     

Modeling the circular economy in environmentally extended input–output: A web application

Global environmental and resource problems ask for new ways of managing the production and consumption of resources. The implementation of new paradigms, such as the circular economy, requires decision‐makers at multiple levels to make complex decisions. For this, clear analyses and modeling of scenarios are of utmost importance. Meanwhile, as the sophistication of databases and models increases so does the need for user‐friendly tools to use them. The RaMa‐Scene web platform reduces these barriers by allowing users to visualize easily diverse impacts of implementing circular‐economy interventions. This online web platform makes use of the multi‐regional environmentally extended input–output database EXIOBASE version 3 in monetary units, which has been modified to show explicit transactions of raw materials from recycling activities.     

Independent sources of condition dependency and multiple pathways determine a composite trait: lessons from carotenoid‐based plumage colouration

Many colour ornaments are composite traits consisting of at least four components, which themselves may be more complex, determined by independent evolutionary pathways, and potentially being under different environmental control. To date, little evidence exists that several different components of colour elaboration are condition dependent and no direct evidence exists that different ornamental components are affected by different sources of variation. For example, in carotenoid‐based plumage colouration, one of the best‐known condition‐dependent ornaments, colour elaboration stems from both condition‐dependent pigment concentration and structural components. Some environmental flexibility of these components has been suggested, but specifically which and how they are affected remains unknown. Here, we tested whether multiple colour components may be condition dependent, by using a comprehensive 3 × 2 experimental design, in which we carotenoid supplemented and immune challenged great tit nestlings (Parus major) and quantified effects on different components of colouration. Plumage colouration was affected by an interaction between carotenoid availability and immune challenge. Path analyses showed that carotenoid supplementation increased plumage saturation via feather carotenoid concentration and via mechanisms unrelated to carotenoid deposition, while immune challenge affected feather length, but not carotenoid concentration. Thus, independent condition‐dependent pathways, affected by different sources of variation, determine colour elaboration. This provides opportunities for the evolution of multiple signals within components of ornamental traits. This finding indicates that the selective forces shaping the evolution of different components of a composite trait and the trait's signal content may be more complex than believed so far, and that holistic approaches are required for drawing comprehensive evolutionary conclusions.     

Corticosterone regulates multiple colour traits in Lacerta [Zootoca] vivipara males

Ornamental colours usually evolve as honest signals of quality, which is supported by the fact that they frequently depend on individual condition. It has generally been suggested that some, but not all types of ornamental colours are condition dependent, indicating that different evolutionary mechanisms underlie the evolution of multiple types of ornamental colours even when these are exhibited by the same species. Stress hormones, which negatively affect condition, have been shown to affect colour traits based on different pigments and structures, suggesting that they mediate condition dependence of multiple ornament types both among and within individuals. However, studies investigating effects of stress hormones on different ornament types within individuals are lacking, and thus, evidence for this hypothesis is scant. Here, we investigated whether corticosterone mediates condition dependence of multiple ornaments by manipulating corticosterone levels and body condition (via food availability) using a two‐factorial design and by assessing their effect on multiple colour traits in male common lizards. Corticosterone negatively affected ventral melanin‐ and carotenoid‐based coloration, whereas food availability did not affect coloration, despite its significant effect on body condition. The corticosterone effect on melanin‐ and carotenoid‐based coloration demonstrates the condition dependence of both ornaments. Moreover, corticosterone affected ventral coloration and had no effect on the nonsexually selected dorsal coloration, showing specific effects of corticosterone on ornamental ventral colours. This suggests that corticosterone simultaneously mediates condition dependence of multiple colour traits and that it therefore accounts for covariation among them, which may influence their evolution via correlational selection.